title: Prognostic and predictive blood-based biomarkers in patients with advanced pancreatic cancer: results from CALGB80303 (Alliance).
abstract: OBJECTIVE
  CALGB80303 was a phase III trial of 602 patients with locally advanced or metastatic pancreatic cancer comparing gemcitabine/bevacizumab versus gemcitabine/placebo. The study found no benefit in any outcome from the addition of bevacizumab to gemcitabine. Blood samples were collected and multiple angiogenic factors were evaluated and then correlated with clinical outcome in general (prognostic markers) and with benefit specifically from bevacizumab treatment (predictive markers).
  
  
  METHODS
  Plasma samples were analyzed via a novel multiplex ELISA platform for 31 factors related to tumor growth, angiogenesis, and inflammation. Baseline values for these factors were correlated with overall survival (OS) using univariate Cox proportional hazard regression models and multivariable Cox regression models with leave-one-out cross validation. Predictive markers were identified using a treatment by marker interaction term in the Cox model.
  
  
  RESULTS
  Baseline plasma was available from 328 patients. Univariate prognostic markers for OS were identified including: Ang2, CRP, ICAM-1, IGFBP-1, TSP-2 (all P < 0.001). These prognostic factors were found to be highly significant, even after adjustment for known clinical factors. Additional modeling approaches yielded prognostic signatures from multivariable Cox regression. The gemcitabine/bevacizumab signature consisted of IGFBP-1, interleukin-6, PDGF-AA, PDGF-BB, TSP-2; whereas the gemcitabine/placebo signature consisted of CRP, IGFBP-1, PAI-1, PDGF-AA, P-selectin (both P < 0.0001). Finally, three potential predictive markers of bevacizumab efficacy were identified: VEGF-D (P < 0.01), SDF1 (P < 0.05), and Ang2 (P < 0.05).
  
  
  CONCLUSIONS
  This study identified strong prognostic markers for pancreatic cancer patients. Predictive marker analysis indicated that plasma levels of VEGF-D, Ang2, and SDF1 significantly predicted for benefit or lack of benefit from bevacizumab in this population.
authors.affiliation: Authors' Affiliations: Division of Medical Oncology; Alliance Statistics and Data Center, Duke University Medical Center; Durham, North Carolina; Section of Hematology/Oncology, University of Chicago Cancer Research Center; Chicago, Illinois; Department of Surgery, Brigham and Women's Hospital & Harvard Medical School; Boston, Massachusetts; Department of Internal Medicine, Ohio State University; Columbus, Ohio; and Division of Medical Oncology, University of California, San Francisco, California.
authors.forename: Andrew B
authors.initials: AB
authors.lastname: Nixon
authors.forename: Herbert
authors.initials: H
authors.lastname: Pang
authors.forename: Mark D
authors.initials: MD
authors.lastname: Starr
authors.forename: Paula N
authors.initials: PN
authors.lastname: Friedman
authors.forename: Monica M
authors.initials: MM
authors.lastname: Bertagnolli
authors.forename: Hedy L
authors.initials: HL
authors.lastname: Kindler
authors.forename: Richard M
authors.initials: RM
authors.lastname: Goldberg
authors.forename: Alan P
authors.initials: AP
authors.lastname: Venook
authors.forename: Herbert I
authors.initials: HI
authors.lastname: Hurwitz
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D061067:Antibodies, Monoclonal, Humanized / Q000008:administration & dosage; D000068258:Bevacizumab; D014408:Biomarkers, Tumor / Q000097:blood; D054377:Chemokine CXCL12 / Q000097:blood*; D017326:Clinical Trials, Phase III as Topic; D003841:Deoxycytidine / Q000008:administration & dosage / Q000031:analogs & derivatives; D005260:Female; D006801:Humans; D053208:Kaplan-Meier Estimate; D008297:Male; D008875:Middle Aged; D009367:Neoplasm Staging; D010190:Pancreatic Neoplasms / Q000097:blood*; D011379:Prognosis; D016016:Proportional Hazards Models; D042643:Vascular Endothelial Growth Factor D / Q000097:blood*; D033921:Vesicular Transport Proteins / Q000097:blood*; D000093542:Gemcitabine
chemical_list: D061067:Antibodies, Monoclonal, Humanized; D014408:Biomarkers, Tumor; D054377:Chemokine CXCL12; C555023:VPS51 protein, human; D042643:Vascular Endothelial Growth Factor D; D033921:Vesicular Transport Proteins; D003841:Deoxycytidine; D000068258:Bevacizumab; D000093542:Gemcitabine